Pyrogallic acid-compatibilized polylactic acid/thermoplastic starch blend produced via one-step twin-screw extrusion.

In this study, a one-step extrusion method is proposed to prepare blended polylactic acid (PLA)/thermoplastic starch (TPS) using a novel plant-derived compatibilizer, pyrogallic acid (PGA), to enhance the PLA/TPS compatibility. The effects of PGA on the mechanical behavior, fractured cross-section morphology, thermal and dynamic mechanical performance, and water resistance of PLA/TPS blends were systematically studied. Results demonstrate that the addition of PGA effectively improves the compatibility between TPS and PLA, resulting in enhanced tensile strength, crystallinity, elongation at break, thermal stability, and hydrophobicity of the blends. Specifically, incorporating 1.5 phr of PGA into the blend system yields the highest values for tensile strength (23.38 MPa) and elongation at break (16.96 %), which are 24.7 % and 233.2 %, respectively, higher than those observed for pure PLA/TPS blends. Furthermore, other properties exhibit obvious improvements upon incorporation of PGA into the blends. This approach provides a promising strategy for enhancing the performance of PLA/TPS blends and expanding their applications in food packaging, agricultural film, etc.

Genome-Wide Analysis of the SRPP/REF Gene Family in Taraxacum kok-saghyz Provides Insights into Its Expression Patterns in Response to Ethylene and Methyl Jasmonate Treatments.

Taraxacum kok-saghyz (TKS) is a model plant and a potential rubber-producing crop for the study of natural rubber (NR) biosynthesis. The precise analysis of the NR biosynthesis mechanism is an important theoretical basis for improving rubber yield. The small rubber particle protein (SRPP) and rubber elongation factor (REF) are located in the membrane of rubber particles and play crucial roles in rubber biosynthesis. However, the specific functions of the SRPP/REF gene family in the rubber biosynthesis mechanism have not been fully resolved. In this study, we performed a genome-wide identification of the 10 TkSRPP and 2 TkREF genes' family members of Russian dandelion and a comprehensive investigation on the evolution of the ethylene/methyl jasmonate-induced expression of the SRPP/REF gene family in TKS. Based on phylogenetic analysis, 12 TkSRPP/REFs proteins were divided into five subclades. Our study revealed one functional domain and 10 motifs in these proteins. The SRPP/REF protein sequences all contain typical REF structural domains and belong to the same superfamily. Members of this family are most closely related to the orthologous species T. mongolicum and share the same distribution pattern of SRPP/REF genes in T. mongolicum and L. sativa, both of which belong to the family Asteraceae. Collinearity analysis showed that segmental duplication events played a key role in the expansion of the TkSRPP/REFs gene family. The expression levels of most TkSRPP/REF members were significantly increased in different tissues of T. kok-saghyz after induction with ethylene and methyl jasmonate. These results will provide a theoretical basis for the selection of candidate genes for the molecular breeding of T. kok-saghyz and the precise resolution of the mechanism of natural rubber production.

Molecular basis for cA6 synthesis by a type III-A CRISPR-Cas enzyme and its conversion to cA4 production.

The type III-A (Csm) CRISPR-Cas systems are multi-subunit and multipronged prokaryotic enzymes in guarding the hosts against viral invaders. Beyond cleaving activator RNA transcripts, Csm confers two additional activities: shredding single-stranded DNA and synthesizing cyclic oligoadenylates (cOAs) by the Cas10 subunit. Known Cas10 enzymes exhibit a fascinating diversity in cOA production. Three major forms-cA3, cA4 and cA6have been identified, each with the potential to trigger unique downstream effects. Whereas the mechanism for cOA-dependent activation is well characterized, the molecular basis for synthesizing different cOA isoforms remains unclear. Here, we present structural characterization of a cA6-producing Csm complex during its activation by an activator RNA. Analysis of the captured intermediates of cA6 synthesis suggests a 3'-to-5' nucleotidyl transferring process. Three primary adenine binding sites can be identified along the chain elongation path, including a unique tyrosine-threonine dyad found only in the cA6-producing Cas10. Consistently, disrupting the tyrosine-threonine dyad specifically impaired cA6 production while promoting cA4 production. These findings suggest that Cas10 utilizes a unique enzymatic mechanism for forming the phosphodiester bond and has evolved distinct strategies to regulate the cOA chain length.

Efficacy and Mechanism of Antibiotic Resistance Gene Degradation and Cell Membrane Damage during Ultraviolet Advanced Oxidation Processes.

Combinations of UV with oxidants can initiate advanced oxidation processes (AOPs) and enhance bacterial inactivation. However, the effectiveness and mechanisms of UV-AOPs in damaging nucleic acids (e.g., antibiotic resistance genes (ARGs)) and cell integrity represent a knowledge gap. This study comprehensively compared ARG degradation and cell membrane damage under three different UV-AOPs. The extracellular ARG (eARG) removal efficiency followed the order of UV/chlorine > UV/H2O2 > UV/peracetic acid (PAA). Hydroxyl radical (•OH) and reactive chlorine species (RCS) largely contributed to eARG removal, while organic radicals made a minor contribution. For intracellular ARGs (iARGs), UV/H2O2 did not remove better than UV alone due to the scavenging of •OH by cell components, whereas UV/PAA provided a modest synergism, likely due to diffusion of PAA into cells and intracellular •OH generation. Comparatively, UV/chlorine achieved significant synergistic iARG removal, suggesting the critical role of the RCS in resisting cellular scavenging and inactivating ARGs. Additionally, flow cytometry analysis demonstrated that membrane damage was mainly attributed to chlorine oxidation, while the impacts of radicals, H2O2, and PAA were negligible. These results provide mechanistic insights into bacterial inactivation and fate of ARGs during UV-AOPs, and shed light on the suitability of quantitative polymerase chain reaction (qPCR) and flow cytometry in assessing disinfection performance.

Genome-Wide Analysis of BBX Gene Family in Three Medicago Species Provides Insights into Expression Patterns under Hormonal and Salt Stresses.

BBX protein is a class of zinc finger transcription factors that have B-box domains at the N-terminus, and some of these proteins contain a CCT domain at the C-terminus. It plays an important role in plant growth, development, and metabolism. However, the expression pattern of BBX genes in alfalfa under hormonal and salt stresses is still unclear. In this study, we identified a total of 125 BBX gene family members by the available Medicago reference genome in diploid alfalfa (Medicago sativa spp. Caerulea), a model plant (M. truncatula), and tetraploid alfalfa (M. sativa), and divided these members into five subfamilies. We found that the conserved motifs of BBXs of the same subfamily reveal similarities. We analyzed the collinearity relationship and duplication mode of these BBX genes and found that the expression pattern of BBX genes is specific in different tissues. Analysis of the available transcriptome data suggests that some members of the BBX gene family are involved in multiple abiotic stress responses, and the highly expressed genes are often clustered together. Furthermore, we identified different expression patterns of some BBX genes under salt, ethylene, salt and ethylene, salicylic acid, and salt and salicylic acid treatments, verified by qRT-PCR, and analyzed the subcellular localization of MsBBX2, MsBBX17, and MsBBX32 using transient expression in tobacco. The results showed that BBX genes were localized in the nucleus. This study systematically analyzed the BBX gene family in Medicago plants, which provides a basis for the study of BBX gene family tolerance to abiotic stresses.

Me-LLaMA: Foundation Large Language Models for Medical Applications.

Recent advancements in large language models (LLMs) such as ChatGPT and LLaMA have hinted at their potential to revolutionize medical applications, yet their application in clinical settings often reveals limitations due to a lack of specialized training on medical-specific data. In response to this challenge, this study introduces Me-LLaMA, a novel medical LLM family that includes foundation models - Me-LLaMA 13/70B, along with their chat-enhanced versions - Me-LLaMA 13/70B-chat, developed through continual pre-training and instruction tuning of LLaMA2 using large medical datasets. Our methodology leverages a comprehensive domain-specific data suite, including a large-scale, continual pre-training dataset with 129B tokens, an instruction tuning dataset with 214k samples, and a new medical evaluation benchmark (MIBE) across six critical medical tasks with 12 datasets. Our extensive evaluation using the MIBE shows that Me-LLaMA models achieve overall better performance than existing open-source medical LLMs in zero-shot, few-shot and supervised learning abilities. With task-specific instruction tuning, Me-LLaMA models outperform ChatGPT on 7 out of 8 datasets and GPT-4 on 5 out of 8 datasets. In addition, we investigated the catastrophic forgetting problem, and our results show that Me-LLaMA models outperform other open-source medical LLMs in mitigating this issue. Me-LLaMA is one of the largest open-source medical foundation LLMs that use both biomedical and clinical data. It exhibits superior performance across both general and medical tasks compared to other open-source medical LLMs, rendering it an attractive choice for medical AI applications. We release our models, datasets, and evaluation scripts at: https://github.com/BIDS-Xu-Lab/Me-LLaMA.

Development of Degraders of Cyclin-Dependent Kinases 4 and 6 Based on Rational Drug Design.

Degradation of target proteins has been considered to be a promising therapeutic approach, but the rational design of compounds for degradation remains a challenge. In this study, we reasonably designed and synthesized only 10 compounds to discover effective CDK4/6 protein degraders. Among the newly synthesized compounds, 7f achieved dual degradation of CDK4/6 protein, with DC50 values of 10.5 and 2.5 nM, respectively. Compound 7f also exhibited inhibitory proliferative activity against Jurkat cells with an IC50 value of 0.18 µM. Furthermore, 7f induced cell apoptosis and G1 phase cell cycle arrest in a dose-dependent manner in Jurkat cells. In conclusion, these findings demonstrate the potential of 7f as a CDK4/6 degrader and a potential therapeutic strategy against cancer, thereby expanding the potential of CDK4/6 dual PROTACs.

Photon-enhanced thermionic emission solar cells based on boron-doped graphene/carbon nanosphere composite aerogel photocathode material.

This study employed a two-step hydrothermal reduction process and freeze-drying technique. Initially, carbon nanosphere composite aerogels (CNSs) were synthesized through the hydrothermal reduction of glucose. Subsequently, boron-doped graphene/carbon nanosphere composite aerogel (BGA/CNS) was prepared by utilizing graphene oxide (GO) and boric acid as carbon (C) and boron (B) sources, respectively, in conjunction with CNS. The photo-enhanced thermionic electron emission (PETE) performance of the samples was assessed using a custom-made device. Boron atom doping was found to modulate the bandgap of graphene aerogel and induce P-type semiconductor characteristics, while the addition of CNSs increased its specific surface area, thereby enhancing its photoelectric properties. The results indicated that BGA/CNS-8h exhibited superior PETE effects, with a short-circuit current, open-circuit voltage, and maximum power of 5.81 µA, -2.10V, and-1.57µW.

Large Language Models for Social Determinants of Health Information Extraction from Clinical Notes - A Generalizable Approach across Institutions.

The consistent and persuasive evidence illustrating the influence of social determinants on health has prompted a growing realization throughout the health care sector that enhancing health and health equity will likely depend, at least to some extent, on addressing detrimental social determinants. However, detailed social determinants of health (SDoH) information is often buried within clinical narrative text in electronic health records (EHRs), necessitating natural language processing (NLP) methods to automatically extract these details. Most current NLP efforts for SDoH extraction have been limited, investigating on limited types of SDoH elements, deriving data from a single institution, focusing on specific patient cohorts or note types, with reduced focus on generalizability. This study aims to address these issues by creating cross-institutional corpora spanning different note types and healthcare systems, and developing and evaluating the generalizability of classification models, including novel large language models (LLMs), for detecting SDoH factors from diverse types of notes from four institutions: Harris County Psychiatric Center, University of Texas Physician Practice, Beth Israel Deaconess Medical Center, and Mayo Clinic. Four corpora of deidentified clinical notes were annotated with 21 SDoH factors at two levels: level 1 with SDoH factor types only and level 2 with SDoH factors along with associated values. Three traditional classification algorithms (XGBoost, TextCNN, Sentence BERT) and an instruction tuned LLM-based approach (LLaMA) were developed to identify multiple SDoH factors. Substantial variation was noted in SDoH documentation practices and label distributions based on patient cohorts, note types, and hospitals. The LLM achieved top performance with micro-averaged F1 scores over 0.9 on level 1 annotated corpora and an F1 over 0.84 on level 2 annotated corpora. While models performed well when trained and tested on individual datasets, cross-dataset generalization highlighted remaining obstacles. To foster collaboration, access to partial annotated corpora and models trained by merging all annotated datasets will be made available on the PhysioNet repository.

The cumulative impact of temperature and nitrogen availability on the potential nitrogen fixation and extracellular polymeric substances secretion by Dolichospermum.

Nitrogen-fixing cyanobacteria not only cause severe blooms but also play an important role in the nitrogen input processes of lakes. The production of extracellular polymeric substances (EPS) and the ability to fix nitrogen from the atmosphere provide nitrogen-fixing cyanobacteria with a competitive advantage over other organisms. Temperature and nitrogen availability are key environmental factors in regulating the growth of cyanobacteria. In this study, Dolichospermum (formerly known as Anabaena) was cultivated at three different temperatures (10 °C, 20 °C, and 30 °C) to examine the impact of temperature and nitrogen availability on nitrogen fixation capacity and the release of EPS. Initially, confocal laser scanning microscopy (CLSM) and the quantification of heterocysts at different temperatures revealed that lower temperatures (10 °C) hindered the differentiation of heterocysts under nitrogen-deprived conditions. Additionally, while heterocysts inhibited the photosynthetic activity of Dolichospermum, the secretion of EPS was notably affected by nitrogen limitation, particularly at 30 °C. Finally, real-time quantitative polymerase chain reaction (qPCR) was used to measure the expression of nitrogen-utilizing genes (ntcA and nifH) and EPS synthesis-related genes (wzb and wzc). The results indicated that under nitrogen-deprived conditions, the expression of each gene was upregulated, and there was a significant correlation between the upregulation of nitrogen-utilizing and EPS synthesis genes (P < 0.05). Our findings suggested that Dolichospermum responded to temperature variation by affecting the formation of heterocysts, impacting its potential nitrogen fixation capacity. Furthermore, the quantity of EPS released was more influenced by nitrogen availability than temperature. This research enhances our comprehension of interconnections between nitrogen deprivation and EPS production under the different temperatures.

Centennial Records of Microplastics in Lake Cores in Huguangyan Maar Lake, China.

Microplastic records from lake cores can reconstruct the plastic pollution history. However, the associations between anthropogenic activities and microplastic accumulation are not well understood. Huguangyan Maar Lake (HML) is a deep-enclosed lake without inlets and outlets, where the sedimentary environment is ideal for preserving a stable and historical microplastic record. Microplastic (size: 10-500 µm) characteristics in the HML core were identified using the Laser Direct Infrared Imaging system. The earliest detectable microplastics appeared unit in 1955 (1.1 items g-1). The microplastic abundance ranged from n.d. to 615.2 items g-1 in 1955-2019 with an average of 134.9 items g-1. The abundance declined slightly during the 1970s and then increased rapidly after China's Reform and Opening Up in 1978. Sixteen polymer types were detectable, with polyethylene and polypropylene dominating, accounting for 23.5 and 23.3% of the total abundance, and the size at 10-100 µm accounted for 80%. Socioeconomic factors dominated the microplastic accumulation based on the random forest modeling, and the contributions of GDP per capita, plastic-related industry yield, and total crop yield were, respectively, 13.9, 35.1, and 9.3% between 1955-2019. The total crop yield contribution further increased by 1.7% after 1978. Coarse sediment particles increased with soil erosion exacerbated microplastics discharging into the sediment.

A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

BACKGROUND: Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic factors contributing to their occurrence, and the identification of underlying causes to refine the NLP model and improve its performance. Conducting error analysis can be complex, requiring a combination of NLP expertise and domain-specific knowledge. Due to the high heterogeneity of electronic health record (EHR) settings across different institutions, challenges may arise when attempting to standardize and reproduce the error analysis process. OBJECTIVES: This study aims to facilitate a collaborative effort to establish common definitions and taxonomies for capturing diverse error types, fostering community consensus on error analysis for clinical concept extraction tasks. MATERIALS AND METHODS: We iteratively developed and evaluated an error taxonomy based on existing literature, standards, real-world data, multisite case evaluations, and community feedback. The finalized taxonomy was released in both .dtd and .owl formats at the Open Health Natural Language Processing Consortium. The taxonomy is compatible with several different open-source annotation tools, including MAE, Brat, and MedTator. RESULTS: The resulting error taxonomy comprises 43 distinct error classes, organized into 6 error dimensions and 4 properties, including model type (symbolic and statistical machine learning), evaluation subject (model and human), evaluation level (patient, document, sentence, and concept), and annotation examples. Internal and external evaluations revealed strong variations in error types across methodological approaches, tasks, and EHR settings. Key points emerged from community feedback, including the need to enhancing clarity, generalizability, and usability of the taxonomy, along with dissemination strategies. CONCLUSION: The proposed taxonomy can facilitate the acceleration and standardization of the error analysis process in multi-site settings, thus improving the provenance, interpretability, and portability of NLP models. Future researchers could explore the potential direction of developing automated or semi-automated methods to assist in the classification and standardization of error analysis.

Lysine 2-hydroxyisobutyrylation proteomics analyses reveal the regulatory mechanism of CaMYB61-CaAFR1 module in regulating stem development in Capsicum annuum L.

Plant stems constitute the most abundant renewable resource on earth. The function of lysine (K)-2-hydroxyisobutyrylation (Khib), a novel post-translational modification (PTM), has not yet been elucidated in plant stem development. Here, by assessing typical pepper genotypes with straight stem (SS) and prostrate stem (PS), we report the first large-scale proteomics analysis for protein Khib to date. Khib-modifications influenced central metabolic processes involved in stem development, such as glycolysis/gluconeogenesis and protein translation. The high Khib level regulated gene expression and protein accumulation associated with cell wall formation in the pepper stem. Specially, we found that CaMYB61 knockdown lines that exhibited prostrate stem phenotypes had high Khib levels. Most histone deacetylases (HDACs, e.g., switch-independent 3 associated polypeptide function related 1, AFR1) potentially function as the "erasing enzymes" involved in reversing Khib level. CaMYB61 positively regulated CaAFR1 expression to erase Khib and promote cellulose and hemicellulose accumulation in the stem. Therefore, we propose a bidirectional regulation hypothesis of "Khib modifications" and "Khib erasing" in stem development, and reveal a novel epigenetic regulatory network in which the CaMYB61-CaAFR1 molecular module participating in the regulation of Khib levels and biosynthesis of cellulose and hemicellulose for the first time.

Toxic mechanisms of the antiviral drug arbidol on microalgae in algal bloom water at transcriptomic level.

Increasing antivirals in surface water caused by their excessive consumption pose serious threats to aquatic organisms. Our recent research found that the input of antiviral drug arbidol to algal bloom water can induce acute toxicity to the growth and metabolism of Microcystis aeruginosa, resulting in growth inhibition, as well as decrease in chlorophyll and ATP contents. However, the toxic mechanisms involved remained obscure, which were further investigated through transcriptomic analysis in this study. The results indicated that 885-1248 genes in algae were differentially expressed after exposure to 0.01-10.0 mg/L of arbidol, with the majority being down-regulated. Analysis of commonly down-regulated genes found that the cellular response to oxidative stress and damaged DNA bonding were affected, implying that the stress defense system and DNA repair function of algae might be damaged. The down-regulation of genes in porphyrin metabolism, photosynthesis, carbon fixation, glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation might inhibit chlorophyll synthesis, photosynthesis, and ATP supply, thereby hindering the growth and metabolism of algae. Moreover, the down-regulation of genes related to nucleotide metabolism and DNA replication might influence the reproduction of algae. These findings provided effective strategies to elucidate toxic mechanisms of contaminants on algae in algal bloom water.

A simplified herbal decoction attenuates myocardial infarction by regulating macrophage metabolic reprogramming and phenotypic differentiation via modulation of the HIF-1α/PDK1 axis.

BACKGROUND: Myocardial infarction (MI) poses a global public health challenge, often associated with elevated mortality rates and a grim prognosis. A crucial aspect of the inflammatory injury and healing process post-MI involves the dynamic differentiation of macrophages. A promising strategy to alleviate myocardial damage after MI is by modulating the inflammatory response and orchestrating the shift from pro-inflammatory (M1) to anti-inflammatory (M2) macrophages, aiming to achieve a reduced M1/M2 ratio. Nuanxinkang (NXK), a simplified herbal decoction, has demonstrated noteworthy cardioprotective, inflammation-regulating, and myocardial energy metabolism-regulating properties. METHODS: In this study, we constructed an MI model by ligating coronary arteries to investigate the efficacy of NXK in improving ventricular remodeling and cardiac function. Mice were administered NXK (1.65 g/kg/d) or an equivalent volume of regular saline via gavage for 28 consecutive days, commencing the day after surgery. Then, we conducted echocardiography to assess the cardiac function, Masson staining to illustrate the extent of myocardial fibrosis, TUNEL staining to reveal myocardial apoptosis, and flow cytometry to analyze the polarization of M1 and M2 macrophages in the hearts. Besides, a lipopolysaccharide (LPS)-induced pro-inflammatory macrophage (M1) polarization model was implemented in RAW264.7 cells to elucidate the underlying mechanism of NXK in regulating macrophage polarization. RAW264.7 cells were pre-treated with or without NXK-containing serum. Oxidative stress was detected by MitoSox staining, followed by Seahorse energy metabolism assay to evaluate alterations in mitochondrial metabolic patterns and ATP production. Both In vivo and in vitro, HIF-1α and PDK1 were detected by fluorescent quantitative PCR and Western blotting. RESULTS: In vivo, MI mice exhibited a decline in cardiac function, adverse ventricular remodeling, and an increase in glycolysis, coupled with M1-dominant polarization mediated by the HIF-1α/PDK1 axis. Notably, robust responses were evident with high-dose NXK treatment (1.65 g/kg/day), leading to a significant enhancement in cardiac function, inhibition of cardiac remodeling, and partial suppression of macrophage glycolysis and the inflammatory phenotype in MI mice. This effect was achieved through the modulation of the HIF-1α/PDK1 axis. In vitro, elevated levels of mitochondrial ROS production and glycolysis were observed in LPS-induced macrophages. Conversely, treatment with NXK notably reduced the oxidative stress damage induced by LPS and enhanced oxidative phosphorylation (OXPHOS). Furthermore, NXK demonstrated the ability to modify the energy metabolism and inflammatory characteristics of macrophages by modulating the HIF-1α/PDK1 axis. The influence of NXK on this axis was partially counteracted by the HIF-1α agonist DMOG. And NXK downregulated PDK1 expression, curtailed glycolysis, and reversed LPS-induced M1 polarization in macrophages, similar to the PDK1 inhibitor DCA. CONCLUSION: In conclusion, NXK protects against MI-induced cardiac remodeling by inducing metabolic reprogramming and phenotypic differentiation of macrophages, achieved through the modulation of the HIF-1α/PDK1 axis. This provides a novel and promising strategy for the treatment of MI.

Effect of surfactant's charge properties on behavior, physiology, and biochemistry and the release of microcystins of Microcystis aeruginosa.

Surfactant pollution is escalatitheng in eutrophic waters, but the effect of surfactant charge properties on the physiological and biochemical properties of toxin-producing microalgae remains inadequately explored. To address this gap, this study explores the effects and mechanisms of three common surfactants-cetyltrimethylammonium bromide (CTAB, cationic), sodium dodecyl sulfate (SDS, anionic), and Triton X-100 (nonionic)-found in surface waters, on the agglomeration behavior, physiological indicators, and Microcystin-LR (MC-LR) release of Microcystis aeruginosa (M. aeruginosa) by using UV-visible spectroscope, Malvern Zetasizer, fluorescence spectrometer, etc. Results suggest that charge properties significantly affect cyanobacterial aggregation and cellular metabolism. The CTAB-treated group demonstrates a ∼5.74 and ∼9.74 times higher aggregation effect compared to Triton X-100 and SDS (300 mg/L for 180 min) due to strong electrostatic attraction. Triton X-100 outperforms CTAB and SDS in polysaccharide extraction, attributed to its higher water solubility and lower critical micelle concentration. CTAB stimulates cyanobacteria to secrete proteins, xanthohumic acid, and humic acids to maintain normal physiological cells. Additionally, the results of SEM and ion content showed that CTAB damages the cell membrane, resulting in a ∼90% increase in the release of intracellular MC-LR without cell disintegration. Ionic analyses confirm that all three surfactants alter cell membrane permeability and disrupt ionic metabolic pathways in microalgae. This study highlights the relationship between the surface charge properties of typical surfactants and the dispersion/agglomeration behavior of cyanobacteria. It provides insights into the impact mechanism of exogenous surfactants on toxic algae production in eutrophic water bodies, offering theoretical references for managing surfactant pollution and treating algae blooms.

Towards elevated perfluorooctanoic acid (PFOA) enrichment in water: Sequential liquid-liquid extraction pretreatment for ion chromatography detection.

The widespread detection of perfluorooctanoic acid (PFOA) in the environment has raised significant concerns. The standard PFOA analytical method relies on expensive solid-phase extraction (SPE) and liquid chromatography tandem mass spectrometry (LC-MS/MS) instruments, making routine use prohibitive. We herein proposed a cost-effective yet novel enrichment method for determining PFOA at ng L-1 level. This method entailed a two-step sample preparation process: firstly, PFOA was extracted and enriched using a forward-extraction under acidic conditions, followed by a backward-extraction and enrichment step utilizing alkaline water. The enriched samples were subsequently subjected to a common ion chromatography (IC). Results reveal that maintaining a forward-extraction pH below its pKa value (2.8) is essential, as protonated PFOA proves effective in enhancing the enrichment factor (EF). The challenge lied in driving PFOA from forward-extractant to aqueous backward-extractant due to the decreased hydrophobicity of deprotonated PFOA (log Kow2 = 1.0). In addition, we found that evaporating forward-extractant with alkaline backward-extractant (containing 5% methanol) reduced potential analytical uncertainties associated with PFOA evaporation and sorption. Under optimal conditions, the method achieved a detection limit of 9.2 ng L-1 and an impressive EF value of 719. Comparison with SPE-LC-MS/MS confirmed the proposed method as a promising alternative for PFOA determination. Although initially targeted for PFOA, the novel methodology is likely applicable to preconcentration of other poly-fluoroalkyl substances.

Helmet wearing detection algorithm based on improved YOLOv5.

In industrial production, workers need to wear safety helmets at all times. However, due to different lighting, viewing angles, and the tendency of people to block each other, the precision of target detection is not high enough. Aiming at this problem, a real-time detection of helmets was achieved by improving the YOLOv5 algorithm. This algorithm introduces the lightweight network structure FasterNet, which uses partial convolution as the main operator to reduce the amount of calculations and parameters of the network; the boundary regression loss function Wise-IoU loss function with a dynamic focusing mechanism replaces the original loss function in YOLOv5; finally, the CBAM attention mechanism is introduced to obtain global context information and improve the detection ability of small targets. The experimental results show that the parameters of the improved YOLOv5 model are reduced by 12.68%, the computational amount is reduced by 10.8%, the mAP is increased from 88.3 to 92.3%, and the inference time is reduced by 81.5%, which is better than the performance of the original model and can detect helmet wearing effectively and in real time.

Interfacial tuning in FeP/ZnIn2S4 Ohm heterojunction: Enhanced photocatalytic hydrogen production via Zn-P charge bridging.

Interfacial regulation is key to photocatalytic performance, yet modulating interfacial charge transfer in heterostructures remains challenging. Herein, a novel nanoflower-like FeP/ZnIn2S4 Ohm heterostructure is first designed, with Zn atoms in ZnIn2S4 (ZIS) acting as potential anchoring sites around P atoms, forming liganded Zn-P bonds. Combining 1D FeP nanowires and 2D ZIS nanosheets enhances the mobility of photogenerated electrons. The synergistic chain-type "electron pickup" mechanism of the Ohm heterojunction coupled with the Zn-P bond speeds up electron transport at the interface. The Ohm heterojunction initiates an internal electric field, creating a driving force to further transfer photogenerated electrons through the Zn-P rapid electron transport channel to FeP, which acts as a reservoir for active sites to release H2. The optimized FeP/ZIS demonstrates a remarkable H2 evolution rate at 4.36 mmol h-1 g-1, 3.6 times that of pristine ZIS. This work provides novel insights into optimizing photocarrier dynamics via interfacial microenvironment modulation.